Fast meningioma segmentation in T1-weighted magnetic resonance imaging volumes using a lightweight 3D deep learning architecture

Automatic and consistent meningioma segmentation in T1-weighted magnetic resonance (MR) imaging volumes and corresponding volumetric assessment is of use for diagnosis, treatment planning, and tumor growth evaluation. We optimized the segmentation and processing speed performances using a large numb...

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Vydané v:	Journal of medical imaging (Bellingham, Wash.) Ročník 8; číslo 2; s. 024002
Hlavní autori:	Bouget, David, Pedersen, André, Hosainey, Sayied Abdol Mohieb, Vanel, Johanna, Solheim, Ole, Reinertsen, Ingerid
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States 01.03.2021
Predmet:	clinical diagnosis meningioma deep learning magnetic resonance imaging three-dimensional segmentation
ISSN:	2329-4302
On-line prístup:	Zistit podrobnosti o prístupe
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